Assessment of Educational Neuromyths among Teachers and Teacher Candidates
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The aim of study is to determine the neuromyth level of teachers and pre-teachers and reveal if there is significant difference in terms of some variables (gender, class, etc.). Research was designed in survey model. The research sample was formed with 241 teachers and 511 teacher candidates. In the collection of data, “Educational neuromyhts test” that has 31 questions with options “right, wrong, I have no idea” that was created by the authors by applying reliability studies. Score that can be taken from measuring tool are in the range of 0-31. According to the findings; while teachers are having an average score of “18,87”, teacher candidates received an average score of “16,70”. According to this result, teacher and teacher candidates have misplaced half of the questions of neurometry. While comparing the scores of teachers and teacher candidates, a significant difference in favor of the teachers (p=.000) were found. The results of the research are expected to led to a debate on “brain and learning” issues.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it